Today, an appropriate automated storm rating system, and specifically an automated, self-sufficient parametric risk-transfer system based on automated recognized or measured storm risk exposures, is painfully lacking. For many countries, with specific topological structural conditions or geographic realities, already providing a technically correct storm rating or measure of storm risk exposure is technically nearly impossible. A glance at the loss history shows that economic losses caused by storms, in particular tropical storms, are as high or higher than those of earthquakes, floods and other perils. For most of these other perils, there are already various rating, forecast, and prediction systems allowing technically the automated risk-transfer by means of appropriately realized self-sufficient risk-transfer systems. Large amounts of money, industrial power and time are lost due to storm events. Additionally, with the trend of increasing risk transfer penetration for storms, the insurance industry and re-insurance industry as well as the countries and its population is affected ever more by storm losses. To extend storm rating and forecasting to detailed predictions and impact measurements, however, the threat of immense quantities of data must be addressed. This is done through completely new concepts on the hazard event side as well as on the system and/or method side.
Storms, and in particular tropical storms such as cyclones, hurricanes, and typhoons, etc., cause severe damage in various parts of the world at regular intervals. Climate change has worsened the situation considerably, causing a wide variety of technical problems, inter alia for precise forecasting systems and adequately signaled intervention systems for physical or monetary intervention to at least mitigate the problems in-situ. Sophisticated forecast systems are the most important technical means to face and mitigate such potential future events in advance. Such systems impact preventive measures and systems, such as steering and initiating fortification measures, actual measures during the occurrence, such as controlling, timing, and steering intervention means, signaling and alarm systems, and finally controlling and steering measures following such a storm event.
In particular, the examples given in this document address storms and tropical storms, whereas specific types of tropical storms such as cyclones, hurricanes and typhoons, etc. can be treated in the same manner. Hurricanes are the most severe category of the meteorological phenomenon known as the “tropical cyclone.” Hurricanes, like all tropical cyclones, include a pre-existing weather disturbance, warm tropical oceans, moisture, and relatively light winds aloft. If the right conditions persist long enough, they can combine to produce the violent winds, incredible waves, torrential rains and floods associated with this phenomenon. Thus, the formation of a tropical cyclone and its growth into a hurricane, for example, requires: 1) a pre-existing weather disturbance; 2) ocean temperatures of at least 26° C. to a depth of about 45 m; and 3) winds that are relatively light throughout the depth of the atmosphere (low wind shear). Typically, tropical storms and hurricanes weaken when their sources of heat and moisture are cut off (as happens when they move over land) or when they encounter strong wind shear. However, a weakening hurricane can reintensify if it moves into a more favorable region. The remnants of a land falling hurricane can still cause considerable damage. Each year, an average of ten tropical storms develop over the Atlantic Ocean, Caribbean Sea and Gulf of Mexico. Many of these remain over the ocean. Six of these storms become hurricanes each year. In an average 3-year period, roughly five hurricanes strike the United States coastline, for instance, killing approximately 50 to 100 people anywhere from Texas to Maine. Of these, two are typically major hurricanes (wind speeds exceeding 110 mph).
However, it is technically difficult, if not impossible, to predict the occurrence of such weather events over the long term and furthermore to forecast and in-depth rate their actual localized impact on the ground. Even with a detailed wind field map, which can not be provided by prior art systems on an aggregated high-resolution grid level for definable territories or counties, the path or movement of an existing storm can also be difficult to predict over a period of hours or days. As an example, consider storm Isaac (AL092012), which lasted from Aug. 21 to Sep. 1, 2012. Isaac was a tropical storm, which became a category 1 hurricane on the Saffir-Simpson Hurricane Wind Scale, just a few hours before landfall in southeastern Louisiana. The tropical cyclone produced heavy rainfall and inland flooding across portions of the Caribbean as it moved through the Lesser Antilles, and it made landfalls along southwestern Haiti and eastern Cuba. Isaac became a large tropical cyclone and caused an extensive storm surge and inland flooding over southern Mississippi and southeastern Louisiana. Isaac is estimated to be directly responsible for 34 deaths, including 24 in Haiti, 5 in the Dominican Republic, and 5 in the United States.
To illustrate the technical problems associated with forecasting and impact rating systems for tropical storms, the synoptic history of Isaac provided below may be useful. It first bears mentioning that one of the problems that comes with capturing and forecasting the development of tropical storms such as Isaac is caused by the finite nature and structure of automated electronically produced systems. Isaac originated from a tropical turbulent flow that moved off the coast of Africa on August 16. A broad area of low pressure developed along the tropical turbulent flow axis south of the Cape Verde Islands on August 17th, but did not develop a well-defined center of circulation until 1200 UTC (Coordinated Universal Time) on August 20 over the central tropical Atlantic. Deep convection became sufficiently organized near the center of the structural low for the system to be classified as a tropical depression at 0600 UTC August 21, when it was centered about 625 n mi east of the Lesser Antilles. The depression strengthened and became a tropical storm 12 hours later, about 450 n ml east of the Lesser Antilles. Isaac's path is illustrated in FIG. 1, showing a diagram schematically illustrating tracking positions of Hurricane Isaac from Aug. 21-Sep. 1, 2012 provided by the NOAA (National Oceanic and Atmospheric Administration) Hydrometeorological Prediction Center. Table 1 gives an overview of the tracked positions and intensities.
TABLE 1tracking for Hurricane Isaac, Aug. 21-Sep. 1, 2012Date/Wind TimeLatitudeLongitudePressureSpeed(UTC)(°N)(°W)(mb)(kt)Stage20/120015.744.8101025Low20/180015.646.8100930″21/000015.248.5100830″21/060014.950.1100730tropical depression21/120015.051.6100630″21/180015.253.1100535tropical storm22/000015.454.8100440″22/060015.756.6100345″22/120015.958.6100445″22/180016.160.4100445″23/000015.762.0100445″23/060015.063.4100445″23/120015.165.0100345″23/180015.666.4100345″24/000015.767.8100245″24/060015.469.199845″24/120015.770.499550″24/180016.671.299355″25/000017.371.899255″25/060018.372.799155″25/120019.673.999750″25/180020.875.299750″26/000021.876.799750″26/060022.778.399555″26/120023.480.099555″26/180023.781.499250″27/000024.282.699050″27/060025.083.698950″27/120015.770.499555″27/180016.671.299360″28/000017.371.899260″28/060018.372.799160″28/120019.673.999765hurricane28/180020.875.299770″29/000021.876.799770″29/030022.778.399570″29/060023.480.099570″29/120023.781.499265″29/180024.282.699060tropical storm30/000025.083.698955″30/060025.784.798755″30/120026.385.798245″30/180026.886.797935″31/000027.487.697830tropical depression31/060028.088.397525″31/120028.688.897220″31/180028.989.496720″01/000029.089.796520″01/060029.190.096620″01/1200dissipated29/030029.089.796570minimum pressure25/060018.372.799155landfall nearJacmel, Haiti25/150020.174.599750landfall near Cajobabo,Guantánamo, Cuba landfall at Southwest29/000028.989.496770Pass at the mouth of the Mississippi River29/080029.290.296670landfall near PortFourchon, Louisiana
The boundary conditions and influences on the path and wind fields of storms, in particular tropical storms, are complex and technically difficult to capture. Continuing the above example, a strong deep-layer subtropical ridge over the western Atlantic caused Isaac to move quickly westward at 15 to 20 kt for the next two days. The center of the tropical storm moved through the Leeward Islands between the islands of Guadeloupe and Dominica between 1800 UTC August 22 and 0000 UTC August 23, but the strongest winds were located well to the north of the center, spreading across the northern Leeward Islands and the Virgin Islands. Isaac continued generally westward over the eastern Caribbean Sea until early on August 24, and aircraft and satellite data indicated that the structure of the cyclone became less organized when the low-level center reformed farther south and the circulation became more tilted. Nonetheless, Isaac strengthened to an intensity of 55 kt on August 24, when it turned northwestward toward Hispaniola. The structure of the cyclone began to improve with the formation of a more developed inner core and the first hints of an eye just before Isaac made landfall on the southern coast of Haiti, near the city of Jacmel, around 0600 UTC on August 25. The center of Isaac quickly traversed the narrow southwestern peninsula of Haiti, and the cyclone weakened slightly when the circulation interacted with the mountainous terrain of Hispaniola. Isaac continued northwestward over the Gulf of Gonâve during the early morning hours of August 25 and moved just south of the Windward Passage, making landfall along the southeastern coast of Cuba near Cajobabo, Guantánamo, around 1500 UTC with maximum winds of 50 kt. The center emerged from the northern coast of Cuba into the Atlantic near Rafael Freyre, Holguin, around 2015 UTC. Isaac grew in size during its passage across Haiti and Cuba, with tropical storm-force winds extending up to 180 n mi to the north of the center across the Turks and Caicos Islands and most of the Bahamas.
After emerging over the Atlantic, Isaac turned west-northwestward and moved faster on August 26 between a large deep-layer low over the northwestern Caribbean Sea and a midtropospheric ridge over the western Atlantic. Isaac had maximum sustained winds of 50 kt while the center moved parallel to the northern coast of Cuba toward the Straits of Florida, passing south of the Florida Keys later in the day. Tropical storm-force winds, especially in gusts, affected the Florida Keys and South Florida in rain bands that moved across the area for much of the day. Isaac entered the southeastern Gulf of Mexico early on August 27, moving more slowly toward the west-northwest and northwest as it reached the southwestern periphery of the subtropical ridge. The wind field remained large, and microwave data indicated that deep convection became more organized in a ring around the center of circulation. Isaac gradually strengthened while moving across the Gulf of Mexico and became a hurricane around 1200 UTC on August 28 while centered about 75 n mi southeast of the mouth of the Mississippi River. A midlevel blocking ridge to the northwest of the hurricane caused Isaac to slow down considerably while it approached the coast of Louisiana, which prolonged the strong winds, dangerous storm surge, and heavy rains along the northern Gulf coast. Isaac made its first landfall along the coast of Louisiana at Southwest Pass on the mouth of the Mississippi River around 0000 UTC on August 29 with maximum sustained winds of 70 kt. The center then wobbled westward back over water and made a second landfall just west of Port Fourchon, La., around 0800 UTC on August 29. Isaac gradually weakened once it moved inland over southeastern Louisiana, and it became a tropical storm at 1800 UTC on August 29, when the center was located about 35 n mi west-southwest of New Orleans. A mid-level anticyclone over the southeastern United States steered Isaac northwestward across Louisiana on August 30, and the cyclone weakened to a tropical depression around 0000 UTC on August 31, just after crossing into southern Arkansas. The depression turned northward and moved into extreme southwestern Missouri later on August 31. The center of circulation then lost its definition over western Missouri early on September 1, and Isaac dissipated just after 0600 UTC about 55 n mi west-southwest of Jefferson City, Mo. The remnants of Isaac moved northeastward and eastward across Missouri and Illinois, producing several tornadoes across the Mississippi River Valley later on September 1.
In prior art systems, such tracking may for example include subjective satellite-based Dvorak technique intensity estimates, for instance from the Tropical Analysis and Forecast Branch (TAFB) and the Satellite Analysis Branch (SAB), and/or objective Dvorak estimates from the Cooperative Institute for Meteorological Satellite Studies/University of Wisconsin-Madison (UW-CIMSS). Other data and images, as shown by FIG. 2, are for example available from NOAA polar-orbiting satellites including the Advanced Microwave Sounding Unit (AMSU), the NASA Tropical Rainfall Measuring Mission (TRMM) and Aqua, the European Space Agency's Advanced Scatterometer (ASCAT), the Naval Research Laboratory WindSat, and/or Defense Meteorological Satellite Program (DMSP) satellites, which can, inter alia, be also useful in constructing an existing track, such as Isaac's track. Another type of data is available from Aircraft observation and measurements including flight-level, stepped frequency microwave radiometer (SFMR), and dropwindsonde observations from flights as for example of the 53rd Weather Reconnaissance Squadron of the U.S. Air Force Reserve Command and/or flights of the NOAA Aircraft Operations Center (AOC) WP-3D aircraft. In the case of Isaac, the 53rd Weather Reconnaissance Squadron and the NOAA AOC G-IV aircraft for example flew respective synoptic surveillance flights around Isaac. Further, national weather services, such as WSR-88D Doppler radar data from San Juan, Puerto Rico; Miami, Fla.; Key West, Fla.; and Slidell, La., can be used to make center fixes and obtain velocity data to track storms, if they are near the coast. Météo-France radar data from Guadeloupe and Martinique, for example, as well as radar data from the Institute of Meteorology of Cuba, for example, can also help to track the center of a tropical storm. Finally, another source of data can be found in ship reports of tropical storm force winds associated with the tropical storm and/or selected surface observations from land stations and data buoys.
Wind and pressures are important parameters for tropical storms. In the above example of Isaac, Isaac's analyzed strengthening to a tropical storm is based on a measured 1500-ft flight level wind of 44 kt at 1843 UTC on August 21, which suggests maximum surface winds of about 35 kt, and on bias-adjusted SFMR estimates of about 35 kt between 1800 and 2000 UTC on August 21. Measurements and estimations of the intensity of tropical storms are complex. Typically, there is a great discrepancy between the flight level and surface estimates, and for example the likelihood that an adjustment of the SFMR estimates does fully account for the peak in rain rates, moreover, when the tropical storm moved across an island or land. The large wind field of a tropical storm can lead to extensive storm surge flooding. In the case of Isaac, Isaac for instance impacted extensive storm surge flooding along the northern Gulf of Mexico coastline, especially in southeastern Louisiana, Mississippi, and Alabama. The highest storm surge measured by a NOS tide gauge was 11.03 ft above normal tide levels at Shell Beach, La., on the southern end of Lake Borgne. A storm surge of 6.69 ft was measured at Pilottown, La., near the mouth of the Mississippi River, and a surge of 6.35 ft was observed in New Orleans at New Canal Station on the southern shore of Lake Pontchartrain. In Mississippi, a storm surge of 8.00 ft was measured by the NOS gauge at the Bay Waveland Yacht Club. Farther east, a storm surge of 4.63 ft was measured in Mobile Bay, Ala., at the Coast Guard Sector Mobile facility. Further, the inundation levels of tropical storms, typically expressed above ground level, can be prevalent near the immediate coast, lakeshore, or levee systems due to the storm tide.
One of the most fundamental problems of the prior art system is that there is no such thing as a true measure of a storm. One impressive example can be given by hurricane Katrina. Hurricane Katrina was the eleventh named storm and fifth hurricane of the 2005 Atlantic hurricane season. It was the costliest natural disaster, as well as one of the five deadliest hurricanes, in the history of the United States. The storm is currently ranked as the third most intense United States land-falling tropical cyclone, behind only the 1935 Labor Day hurricane and Hurricane Camille in 1969. The problem was that when hurricane Katrina surged towards New Orleans, people faced the prospect of abandoning their homes to find shelter. Those worst affected were some of the city's most vulnerable citizens, the poor and the elderly, parents with young children, people without cars, and people living in flood-prone areas. Yet Katrina, which was in fact a category 5 storm, was demoted to a category 3 by the time it hit land. However, the forecasting and rating systems were mistaken, since the category rating of the hurricane was not the best measure of the raw destructive power of the storm. So many people, governments and industries did not take the right measures to prevent the catastrophe. As a result of the forecasting systems not correctly capturing the impact of the tropical storm, at least 1,833 people died in the hurricane and subsequent floods, making it the deadliest United States hurricane since the 1928 Okeechobee hurricane. Total property damage was estimated at $108 billion (2005 USD), roughly four times the damage wrought by Hurricane Andrew in 1992. Later, Hurricane Ike in 2008 and Hurricane Sandy in 2012 caused more damage than Hurricane Andrew, but both were far less destructive than Katrina. The hurricane Katrina surge protection failures in New Orleans are considered the worst civil engineering disaster in U.S. history and prompted a lawsuit against the U.S. Army Corps of Engineers (USACE), the designers and builders of the levee system as mandated by the Flood Control Act of 1965.
In the prior art systems, in particular in the western hemisphere, hurricanes are rated on the Saffir-Simpson scale, an empirical measure of storm intensity. To trigger a storm's category rating, the systems measure the highest speed sustained by a gust of wind for an entire minute. The wind's speed is measured at a height of 10 meters because wind speeds increase in relation to the height where they are measured, and it is typically in the vicinity of 10 meters that storms do the most damage. Based on how large this maximum speed is, a storm is assigned in the Saffir-Simpson rating to one of five different categories. The following table 2 shows the Saffir-Simpson rating system.
TABLE 2Saffir-Simpson hurricane wind scaleCategoryWind speedSaffir-Simpson rating systemFive≥70 m/s, ≥137 knots≥157 mph, ≥252 km/hFour58-70 m/s, 113-136 knots130-156 mph, 209-251 km/hThree50-58 m/s, 96-112 knots111-129 mph, 178-208 km/hTwo43-49 m/s, 83-95 knots96-110 mph, 154-177 km/hOne33-42 m/s, 64-82 knots74-95 mph, 119-153 km/hFurther important classificationsTropical storm18-32 m/s, 34-63 knots111-129 mph, 63-118 km/hTropical depression≤17 m/s, ≤33 knots≤38 mph, ≤62 km/h
The Saffir-Simpson Hurricane Scale (SS-Scale) system allows a rough estimation of possible impacts of a tropical storm. As seen above, the SS-scale defines hurricane intensify by categories. A Category 1 storm is the weakest hurricane (winds 64-82 kt); a Category 5 hurricane is the strongest (winds exceeding 135 kt). With respect to the damage caused, it can be said that typically, Category 1 storms with winds between 64-82 kt can normally cause no real damage to building structures. Damage is primarily to unanchored mobile homes, shrubbery and trees. There can be also be some coastal flooding and minor pier damage. Category 2 storms with winds between 83-95 kt can normally cause some roofing material, door and window damage. There can also be considerable damage to vegetation, mobile homes, etc., or flooding damages piers and small craft in unprotected moorings may break their moorings. Category 3 storms, with winds between 96-113 kt, can normally cause some structural damage to small residences and utility buildings, with a minor amount of curtainwall failures. Mobile homes are destroyed. Also, flooding near the coast destroys smaller structures, while larger structures are damaged by floating debris. Terrain may be flooded well inland. Category 4 storms, with winds between 114-135 kt, can normally cause more extensive curtainwall failures with some complete roof structure failure on small residences. There can be also major erosion of beach areas. Terrain may be flooded well inland. Finally, Category 5 storms, with winds of 135+ kt, can normally cause complete roof failure on many residences and industrial buildings. There may be some complete building failures, with small utility buildings blown over or away. Flooding causes major damage to lower floors of all structures near the shoreline. Massive evacuation of residential areas may be required.
The problem with such prior art systems is that they only capture one aspect of a storm's intensity—the highest speed that if can sustain. Not only is it difficult to measure the appropriate peak speed, but different organizations typically come to different conclusions about it, depending on their coverage of the wind data. This number doesn't reveal anything about the size of the storm, or about how the wind speeds are distributed overall. An example can be given by considering the existence of two storms—the first is fierce but more contained, while the second is larger, and though it has lower peak wind speed, these wind speeds are spread over a larger area. The Saffir-Simpson scale would give the first storm a higher score, even though the latter may be more destructive. Based on the rating, people were misled in their expectation about Katrina. Therefore, the rating system based on the SS scale is too simplistic, indicating that the scale takes into account neither the physical size of a storm nor the amount of precipitation it produces. Additionally, the Saffir-Simpson scale-based system, unlike the Richter scale used to measure earthquakes, is not continuous, and is quantized into a small number of categories. Proposed replacement classifications include the Hurricane Intensity Index, which is based on the dynamic pressure caused by a storm's winds, and the Hurricane Hazard Index, which bases itself on surface wind speeds, the radius of maximum winds of the storm, and its translational velocity. Both of these scales are continuous, akin to the Richter scale; however, neither of these scales has been used efficiently up to now.
It is one aim of this invention to provide a reliable, localized measure of a storm. Storms are dangerous because of the energy carried in the moving air. In a storm, strong winds ram into stationary objects, such as trees, buildings, or the surface of the ocean, and impart some of their energy of motion. Some structures can safely absorb this energy, while others will give way. Tropical storms, in particular hurricanes, create a vortex. Vortices are a consequence of the non-linear equations that govern the flow of fluids. In normal situations, these vortices die out, as their energy drains out to the fluid around them. But hurricanes are self-sustaining, fed by evaporating columns of air rising from warm ocean water. Prior art systems, based solely on mathematical simulation, typically fail to model the dynamics of hurricanes adequately. The simulations are complex. On a larger scale, they have to capture the flow of the atmosphere that is responsible for steering the hurricane. On a finer scale, they have to capture the interactions near the core that give the storm its strength. Normally, they try to add just enough essential simulation to reproduce the behavior of the storm, while leaving out the details that will make it impossible to run the simulation with available processor power.
Moreover, correctly forecasting a storm, i.e., its local wind speeds, is only half of the problem. The other part is to forecast how destructive it will be. The storms' strength affects other objects, since every object in motion carries a certain amount of energy, known as its kinetic energy. The kinetic energy of an object depends on the square of its speed, and is directly proportional to the mass of the object. More simply put, it can be assumed that the wind energy over the real size of a storm is related to its true destructive potential. What makes this method very different from the SS scale is that different sizes of wind fields, having the same or different wind speeds, must be appropriately additively captured, which is much more than just the peak intensity of a storm. Therefore, the forecasted parameters must at least take into account how the wind speeds are distributed throughout the bulk of a storm. Some prior art forecasting systems, such as the National Oceanic and Atmospheric Administration, try to measure the strength of a storm by using the so-called integrated kinetic energy of the storm at a certain location. However, these systems also fail to predict the impact correctly, since they do not take the local topological background of the structure into account and are necessarily based on simulations, which then face the same technical problems as described above.
Another aspect is, that automated risk transfer systems, such as automated insurance systems, need to develop ways of assessing and parameterizing the risks associated with such weather events, and factoring that knowledge into the pricing of insurance products and the magnitudes and frequencies of damage to expect over time. Information is available for use in this regard in the form of historical data on storms, which have, occurred through the years. Approximately 80 such storms occur worldwide each year. Data is collected for the storms including positional data for the storm path or track, wind speeds, barometric pressures, and other factors. Such storms are best documented in the North Atlantic (i.e., the portion of the Atlantic Ocean north of the equator), where reliable data covering more than 100 years of activity is available. Approximately 10 storms occur in the North Atlantic region on an annual basis. Historical data is also available for cyclones occurring in the Northwest Pacific, where approximately 26 storms occur each year. Suitable data for these Pacific storms is available only for about the last 50 years. Less data is available for storms in other regions. Using all available historical data, information relating to a few hundred storms is available for review by engineers and scientists for appropriate system design. Such information is useful in assessing risks associated with storm damage in the subject areas. However, given the unpredictable nature of storm behavior, and the number of factors influencing such behaviors, the available data set of historical storms is relatively small from a probabilistic viewpoint. Given that this data set will grow by only a relatively small number of storms per year, a problem exists with regard to performing statistical analysis relating to the possibility of a storm occurring in a particular location.
In summary, in the prior art, existing systems are not able to account correctly for the physical size of a storm, the amount of precipitation it produces, and the effective impact on local structures. Further, they cannot provide a true forecasted measure of a storm and impact rating on an aggregated high-resolution grid level for predefined territory cells and/or counties, which can appropriately be used for corresponding alarm systems and means, damage prevention systems, damage protection systems and/or automated risk transfer systems.